A spatiotemporal analysis of oil spill severity using a multi-criteria decision framework

Abstract

The evaluation of oil spills and their coastal impacts remains a fundamental scientific challenge. This includes the prediction and subsequent evaluation of environmental damage caused by the spills, the development of impact mitigation and cleanup tactics, as well as community preparedness strategies. Much of the recent scientific research in this domain leverages case studies based on spill simulations to demonstrate the effectiveness of the predictive models and methods and their implications for community response. Although many of these studies provide a good snapshot of anticipated consequences of an oil spill at a singular moment in time and in a specific place – the need to evaluate changes in impact at different times and locations remains a fundamental aspect for response policy and contingency planning. The purpose of this paper is to improve the fidelity of spill evaluations, response, and preparedness by using the Technique for Order of Preference by Similarity to Ideal Solutions (TOPSIS) method. In short, TOPSIS is used to rank and compare the spatiotemporal dynamics of spill impacts. It also provides a means for evaluating worst case discharge scenarios. The results of this work can help inform response preparedness by highlighting the geographic and seasonal nuances of potential spill impacts while also detailing an objective approach to ranking oil spill severity.